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Purpose: The present study is about generating metadata to enhance thematic transparency and facilitate research on interview collections at the Research Documentation Centre, Centre for Social Sciences (TK KDK) in Budapest. It explores the use of artificial intelligence (AI) in producing, managing and processing social science data and its potential to generate useful metadata to describe the contents of such archives on a large scale. Design/methodology/approach: The authors combined manual and automated/semi-automated methods of metadata development and curation. The authors developed a suitable domain-oriented taxonomy to classify a large text corpus of semi-structured interviews. To this end, the authors adapted the European Language Social Science Thesaurus (ELSST) to produce a concise, hierarchical structure of topics relevant in social sciences. The authors identified and tested the most promising natural language processing (NLP) tools supporting the Hungarian language. The results of manual and machine coding will be presented in a user interface. Findings: The study describes how an international social scientific taxonomy can be adapted to a specific local setting and tailored to be used by automated NLP tools. The authors show the potential and limitations of existing and new NLP methods for thematic assignment. The current possibilities of multi-label classification in social scientific metadata assignment are discussed, i.e. the problem of automated selection of relevant labels from a large pool. Originality/value: Interview materials have not yet been used for building manually annotated training datasets for automated indexing of scientifically relevant topics in a data repository. Comparing various automated-indexing methods, this study shows a possible implementation of a researcher tool supporting custom visualizations and the faceted search of interview collections. [ABSTRACT FROM AUTHOR]

This is a study of an action research project conducted in one of the biggest university departments for sociology in a Central Eastern European capital during the first half of the 2000s. The paper shows that researchers' images of society have a strong impact on social scientific methodology, scientific explanations and narratives. I offer an example of how realist approaches to science and technology studies can be used in a field study and discuss the benefits and limitations of such an endeavor, which I define as an interpretive and explanatory social scientific work. The analysis shows ways in which latent knowledge structures influenced the wording of a questionnaire used in the research, the types of data that were gathered, and how the data were interpreted. These knowledge structures include notions concerning local policy discussions, different social policy traditions, and images of a Roma minority struggling with the effects of structural poverty and prejudices. [ABSTRACT FROM AUTHOR]

The aim of this article is to present and study how a digital archive can shape and create new ways of producing, publishing, and studying historical sources. Based on our analysis of the COURAGE (Cultural Opposition—Understanding the CultuRal HeritAGE of Dissent in the Former Socialist Countries) Registry about cultural dissent under state socialism in Eastern Europe in the second half of the twentieth century (and focusing on collections about environmental issues in this registry), we seek to understand how different private, amateur, and professional archivists have shaped the scientific and public legacy of cultural dissent under state socialism. The COURAGE Registry conveys a unique view of the history of the Soviet Bloc, providing an assemblage of documents concerning people, groups, institutions, events, and pieces from the time. Together, they tell an alternative story of cultural opposition under socialism, shedding light on important—but until now marginalized—problems, topics, and actors. Our results have shown that cultural opposition in the Registry is understood and constructed as a wide range of forms of engagement and activities, and it is not limited to specific high-cultural or direct political products. The structure of the COURAGE Registry creates a balance among collections that are very diverse in form, and its linked data structure helps connect the information and stories compiled in it. The COURAGE Registry enables researchers to use it as a tool with which to build their own scientific narratives about dissent under socialism. [ABSTRACT FROM AUTHOR]

We experience a strengthening trend of making research publications and research data public; data archiving and data curation activities are becoming an organic part of research work; and the idea of secondary use in research is changing. As a consequence, institutional and national data banks, repositories are being created all over the world (in Hungary, too) in an increasing number, in the field of social sciences as well. The Research Documentation Centre (KDK) of the Hungarian Academy of Sciences Social Science Research Centre, established in 2013, is an open and curated institutional repository, providing access to social science research collections. It soon became a Qualified Repository of the Hungarian Academy of Sciences. The article presents the main objectives and operational principles of KDK, and, through its experience, the opportunities for documenting social science research and for transparent data management. [ABSTRACT FROM AUTHOR]

Following Derrida (1995), our article explores the relationship between archival practices and archival documents on the assumption that “archivization produces as much as it records the event” (Derrida 1995, 17). On this approach, archival practices are understood as non-innocent practices that, in the act of “preservation,” help make specific “memories” at the expense of others (Barad 2007; Derrida 1995; Foucault 1972). We take up this issue in relation to the curation of social science quantitative research data and argue that the ontological identity of data is constituted through historically- and culturally-specific data curation practices including data cleaning, data anonymization, and metadata preparation. [ABSTRACT FROM AUTHOR]

In Hungary, like in many of the former socialist countries, regardless of ongoing research projects based on qualitative data, archives of such research data are sporadic and fragmented. The strong tradition of sociological research produced a vast amount of qualitative social data but no infrastructure was developed to capture, organize and make available these data sets for further analysis. In most cases the secondary analysis or the long-term preservation of these valuable collections is hindered by institutional and disciplinary boundaries as well as a culture of unwillingness to share data in the humanities and social sciences. In Hungary future progress can only be expected if legal barriers are removed or addressed at the policy level; if the underlying infrastructure offers an attractive set of tools for future data collectors; if potential researcher's become aware of the improved access to data; and finally, if preservation best practices, standards, and benchmarking are spread among custodians of the content. It remains an open question which approach is more appropriate: creating a central data repository or setting up a decentralized network of institutions and individuals which can lead to inter-operable platforms to share content and know-how. [ABSTRACT FROM AUTHOR]